Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

RNA-sequencing of tumor infiltrating cells across 12 different solid tumors type

ABSTRACT: To identify patterns of gene expression within six broadly defined cell populations, we also performed cell sorting for bulk RNA-sequencing including compartments denoted: 1. “Live”: All viable cells at the time of sorting, 2. “Tconv”: sorted conventional CD4+ and CD8+ T cells, 3. “Treg”: CD25+ CD4+ (enriched for regulatory) T cells, 4. “Myeloid”: Lymphocyte-negative HLA-DR+ (enriched for myeloid) cells, 5. “Stromal”: CD45- CD44+Thy1+ cells, and 6. “Tumor”: all other CD45- cells

ORGANISM(S): Homo sapiens

PROVIDER: GSE184398 | GEO | 2021/12/29

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Sequencing of tumor associated (B16f10-OVA) mir-155 Wt or deficient CD4+ and CD8+ T cells

Project description:Tumor associated CD4+ and CD8+ T cells were sorted from B16f10 OVA expressing tumors in miR-155 flox, miR-155 flox CD4Cre+, and miR-155 flox CD4Cre+ mice treated with immune checkpoint blocking (ICB) antibodies by flow sorting on CD45+CD3+CD4+ cells and CD45+ CD3+CD8+ cells. RNA was collected from these cells to perform RNA sequencing of total RNA.

2017-09-11 | GSE101690 | GEO

Expression anlysis of E10.5 yolk sac and E13.5 liver lineages from the wildtype mouse embryo

Project description:Single cell suspensions of E10.5 yolk sac cells and E13.5 fetal liver cells were purified by flow cytometry into the following immunophenotypically defined populations: (A) E10.5 diploid platelet-forming cells (megakaryocytic lineage, CD45-CD144-CD41high), E10.5 haematopoietic progenitor cells (CD45+CD41low), E10.5 myeloid cells (CD45+CD41low), and E10.5 endothelium (CD45-CD144+CD41-); and, (B) E13.5 megakaryocytes (CD61-enriched CD41+CD150+CD42D+), myeloid cells (CD45+CD11B+), and blast cells (CD45+CD11B-).

2014-07-27 | E-MTAB-2625 | biostudies-arrayexpress

Kinetic analysis of the response to anti-CD3 in conventional and regulatory CD4+ T cells, in mice and in vitro.

Project description:Several clinical trials have shown anti-CD3 treatment to be a promising therapy for autoimmune diabetes, but its mechanism of action remains unclear. Foxp3+ regulatory T (Treg) cells are likely to be involved, and we have shown a strong effect of anti-CD3 on homeostatic control of CD4+ FoxP3+ regulatory T (Treg) cells. To analyze the early consequences of anti-CD3 treatment, we sorted and profiled Treg and conventional CD4+ T (Tconv) cells in the first hours and days after anti-CD3 treatment of NOD mice. In practice, NOD mice carrying the Foxp3-GFP reporter were treated with anti-CD3 mAb KT3 (50 ug iv) and CD4+ T cells were sorted from pooled spleen and lymph nodes after 2, 8, 24 and 72 hrs, separating Treg and Tconv cells on the basis of GFP expression. Anti-CD3 treatment led to a transient transcriptional response, terminating faster than most antigen-induced responses. Most transcripts were similarly induced in Treg and Tconv cells, but several were differential, in particular those encoding the IL7 receptor (IL7R) and transcription factors Id2/3 and Gfi1, upregulated in Treg but repressed in Tconv cells. In parallel experiments, we tested the effect of soluble anti-CD3 added to cultures of fresh splenocytes, sorting Treg and Tconv cells at the same time points. Many of the anti-CD3 elicited changes, and of the differential response observed in vivo, were also observed in vitro. Two independent replicate series; Treg and Tconv samples abbreviated TR and TC, respectively. Keywords: Transcriptional activation, TCR All gene expression profiles were obtained from highly purified T cell populations sorted by flow cytometry. RNA from 5 x 104 cells was amplified, labeled, and hybridized to Affymetrix ST1.0 Gene arrays. Raw data were preprocessed with the RMA algorithm in GenePattern, and averaged expression values were used for analysis.

2013-07-01 | E-GEOD-48210 | biostudies-arrayexpress

Proteomics reveals unique identities of human TGF-β-induced and thymus-derived CD4+ regulatory T cells

Project description:The CD4+ regulatory T (Treg) cell lineage comprises thymus-derived (t)Treg cells and peripherally induced (p)Treg cells. As a model for Treg cells, studies employ TGF-β-induced (i)Treg cells generated from CD4+ conventional T (Tconv) cells in vitro. Here, we describe the relationship of iTreg cells to tTreg and Tconv cells. Proteomic analysis revealed that iTreg, tTreg and Tconv cell populations each have a unique protein expression pattern. iTreg cells had very limited overlap in protein expression with tTreg cells, regardless of cell activation status and instead shared signaling and metabolic proteins with Tconv cells. tTreg cells had a uniquely modest response to CD3/CD28-mediated stimulation. As a benchmark, we used a previously defined proteomic signature that sets ex vivo naïve and effector phenotype Treg cells apart from Tconv cells and includes unique Treg cell properties (Cuadrado et al., Immunity, 2018). This Treg cell core signature was largely absent in iTreg cells. We also used a proteomic signature that distinguishes ex vivo effector Treg cells from Tconv cells and naïve Treg cells. This effector Treg cell signature was partially present in iTreg cells. In conclusion, iTreg cells are distinct from tTreg cells and share limited features with ex vivo Treg cells at the proteomic level.

2022-11-28 | PXD038302 | Pride

GBM microglia

Project description:High grade glioma in mice and human have been shown to be greatly impacted by the infiltration of macrophages in the tumor, but it is unknown whether the populations of macrophages in the tumors may have different roles in the tumor. Flow sorting and high throughput RNA-seq was employed to examine the two main populations of macrophages in the high grade mouse glioma, denoted by the high or low surface expression of CD45, and they were compared to the resident population of microglia in normal brain tissues that express low levels of CD45.

2019-02-27 | GSE65868 | GEO

Kinetic analysis of the response to anti-CD3 in conventional and regulatory CD4+ T cells, in mice and in vitro.

2013-07-01 | GSE48210 | GEO

Treg cell gene expression signature in B16 melanoma

Project description:Gene expression signature of Treg cells in B16 melanoma was measured and compared to B16-infiltrating CD4+ Tconv cells and CD8+ T cells as well as splenic Treg cells, CD4+ Tconv cells and CD8+ T cells.

2016-10-31 | GSE87335 | GEO

Expression Data of Treg and Tconv Cells from FoxP3-GFP Chimeric and FoxP3-ires-GFP B6 and NOD Mice

Project description:The aim of this study was to quantify the impact of chimeric Foxp3-GFP protein on the Treg cell transcriptional program. Duplicate samples of Tconv (CD3+CD4+GFP-) and Treg (CD3+CD4+GFP+) splenocytes were double-sorted to achieve > 99.0% purity, from 6 weeks old male Foxp3-Fusion-GFP and Foxp3-ires-GFP mice of both B6 and NOD backgrounds. Following cell sorting into Trizol, RNA was purified, labeled and hybridized to Affymetrix arrays.

2012-04-26 | E-GEOD-37605 | biostudies-arrayexpress

Transcription profiling of mouse fat derived flow sorted Treg cells

Project description:Comparisons of global gene-expression profiles revealed a greater distinction between CD4+ Treg cells and CD4+ conventional (Tconv) T cells residing in abdominal (epidydimal) fat versus in more standard locations such as the spleen, thymus and LN. Experiment Overall Design: All gene expression profiles were obtained from highly purified T cell populations sorted by flow cytometry. To reduce variability, cells from multiple mice were pooled for sorting, and three replicates were generated for all groups. RNA from 3-5 x 104 cells was amplified, labeled, and hybridized to Affymetrix M430v2 microarrays. Raw data were preprocessed with the RMA algorithm in GenePattern, and averaged expression values were used for analysis.

2009-08-07 | E-GEOD-7852 | biostudies-arrayexpress

Immune Gene Expression Profile of Conventional and Regulatory T cells

Project description:Understanding human regulatory T cells (Tregs) heterogeneity may identify markers of disease pathogenesis and facilitate the development of optimized cellular therapeutics. To better elucidate human Treg subsets, we conducted direct transcriptional profiling of CD4+FOXP3+Helios+ thymic-derived Treg (tTreg) and CD4+FOXP3+Helios- peripherally-induced Treg (pTreg), followed by comparison to CD4+FOXP3-Helios- T conventional (Tconv) cells. This analysis revealed that the coinhibitory receptor T-cell immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domain (TIGIT) was highly expressed on tTreg. In this study CD4 T cells were stained for the Treg-associated transcription factors FOXP3 and Helios, and subsequently FACS sorted to yield three populations: tTreg (CD4+FOXP3+Helios+), pTreg (CD4+FOXP3+Helios–) and the reference population Tconv (CD4+FOXP3–Helios–). A direct transcriptional profile was obtained from the recovered RNA from the populations defined as tTreg, pTreg, and Tconv.

2015-04-30 | E-GEOD-61834 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data